Bi-directional 3D auto-regressive model approach to motion picture restoration. - Wooi Boon Goh; Man-Nang Chong; Showbhik Kalra; Dilip Krishnan (ICASSP, 1996)

A new spatio-temporal MRF model for the detection of missing data in image sequences. - Man-Nang Chong; P. Liu; Wooi Boon Goh; Dilip Krishnan (ICASSP, 1997)

A new auto-regressive (AR) model-based algorithm for motion picture restoration. - Showbhik Kalra; Man-Nang Chong; Dilip Krishnan (ICASSP, 1997)

An edge-preserving MRF model for the detection of missing data in image sequences. - Man-Nang Chong; Dilip Krishnan (IEEE Signal Process. Lett., 1998)

A MRF Model Based Scheme for Accurate Detection and Adaptive Interpolation of Missing Data in Highly Corrupted Image Sequences. - Showbhik Kalra; Dilip Krishnan; Man-Nang Chong (ICIP (2), 1999)

On the computational aspects of Gibbs-Markov random field modeling of missing-data in image sequences. - Dilip Krishnan; Man-Nang Chong; Showbhik Kalra (IEEE Trans. Image Process., 1999)

A Primal-Dual Active-Set Method for Non-Negativity Constrained Total Variation Deblurring Problems. - Dilip Krishnan; Ping Lin; Andy M. Yip (IEEE Trans. Image Process., 2007)

Fast Image Deconvolution using Hyper-Laplacian Priors. - Dilip Krishnan; Rob Fergus (NIPS, 2009)

A primal-dual active-set algorithm for bilaterally constrained total variation deblurring and piecewise constant Mumford-Shah segmentation problems. - Dilip Krishnan; Quang Vinh Pham; Andy M. Yip (Adv. Comput. Math., 2009)

Dark flash photography. - Dilip Krishnan; Rob Fergus (ACM Trans. Graph., 2009)

Deconvolutional networks. - Matthew D. Zeiler; Dilip Krishnan; Graham W. Taylor; Robert Fergus (CVPR, 2010)

Blind deconvolution using a normalized sparsity measure. - Dilip Krishnan; Terence Tay; Rob Fergus (CVPR, 2011)

Multigrid and multilevel preconditioners for computational photography. - Dilip Krishnan; Richard Szeliski (ACM Trans. Graph., 2011)

Restoring an Image Taken through a Window Covered with Dirt or Rain. - David Eigen; Dilip Krishnan; Rob Fergus (ICCV, 2013)

Blind Deconvolution with Re-weighted Sparsity Promotion. - Dilip Krishnan; Joan Bruna; Rob Fergus (CoRR, 2013)

Efficient preconditioning of laplacian matrices for computer graphics. - Dilip Krishnan; Raanan Fattal; Richard Szeliski (ACM Trans. Graph., 2013)

Low-level Image Priors and Laplacian Preconditioners for Applications in Computer Graphics and Computational Photography. - Dilip Krishnan (2013)

Crisp Boundary Detection Using Pointwise Mutual Information. - Phillip Isola; Daniel Zoran; Dilip Krishnan; Edward H. Adelson (ECCV (3), 2014)

Shape and Illumination from Shading using the Generic Viewpoint Assumption. - Daniel Zoran; Dilip Krishnan; José Bento 001; Bill Freeman (NIPS, 2014)

Reflection removal using ghosting cues. - Yichang Shih; Dilip Krishnan; Frédo Durand; William T. Freeman (CVPR, 2015)

Learning Ordinal Relationships for Mid-Level Vision. - Daniel Zoran; Phillip Isola; Dilip Krishnan; William T. Freeman (ICCV, 2015)

Learning visual groups from co-occurrences in space and time. - Phillip Isola; Daniel Zoran; Dilip Krishnan; Edward H. Adelson (CoRR, 2015)

Domain Separation Networks. - Konstantinos Bousmalis; George Trigeorgis; Nathan Silberman; Dilip Krishnan; Dumitru Erhan (NIPS, 2016)

Unsupervised Pixel-Level Domain Adaptation with Generative Adversarial Networks. - Konstantinos Bousmalis; Nathan Silberman; David Dohan; Dumitru Erhan; Dilip Krishnan (CVPR, 2017)

Synthesizing Normalized Faces from Facial Identity Features. - Forrester Cole; David Belanger 002; Dilip Krishnan; Aaron Sarna; Inbar Mosseri; William T. Freeman (CVPR, 2017)

Learning to Count Mosquitoes for the Sterile Insect Technique. - Yaniv Ovadia; Yoni Halpern; Dilip Krishnan; Josh Livni; Daniel E. Newburger; Ryan Poplin; Tiantian Zha; D. Sculley (KDD, 2017)

Face Synthesis from Facial Identity Features. - Forrester Cole; David Belanger 002; Dilip Krishnan; Aaron Sarna; Inbar Mosseri; William T. Freeman (CoRR, 2017)

Smart, Sparse Contours to Represent and Edit Images. - Tali Dekel; Chuang Gan 001; Dilip Krishnan; Ce Liu 001; William T. Freeman (CoRR, 2017)

Sparse, Smart Contours to Represent and Edit Images. - Tali Dekel; Chuang Gan 001; Dilip Krishnan; Ce Liu 001; William T. Freeman (CVPR, 2018)

Large Margin Deep Networks for Classification. - Gamaleldin F. Elsayed; Dilip Krishnan; Hossein Mobahi; Kevin Regan 001; Samy Bengio (NeurIPS, 2018)

Visualizing Dataflow Graphs of Deep Learning Models in TensorFlow. - Kanit Wongsuphasawat; Daniel Smilkov; James Wexler; Jimbo Wilson; Dandelion Mané; Doug Fritz; Dilip Krishnan; Fernanda B. Viégas; Martin Wattenberg (IEEE Trans. Vis. Comput. Graph., 2018)

Boundless: Generative Adversarial Networks for Image Extension. - Dilip Krishnan; Piotr Teterwak; Aaron Sarna; Aaron Maschinot; Ce Liu 001; David Belanger 002; William T. Freeman (ICCV, 2019)

Predicting the Generalization Gap in Deep Networks with Margin Distributions. - Yiding Jiang; Dilip Krishnan; Hossein Mobahi; Samy Bengio (ICLR (Poster), 2019)

Adversarial Robustness through Local Linearization. - Chongli Qin; James Martens; Sven Gowal; Dilip Krishnan; Krishnamurthy Dvijotham; Alhussein Fawzi; Soham De; Robert Stanforth; Pushmeet Kohli (NeurIPS, 2019)

A Closed-Form Learned Pooling for Deep Classification Networks. - Vighnesh Birodkar; Hossein Mobahi; Dilip Krishnan; Samy Bengio (CoRR, 2019)

Contrastive Multiview Coding. - Yonglong Tian; Dilip Krishnan; Phillip Isola (ECCV (11), 2020)

Rethinking Few-Shot Image Classification: A Good Embedding is All You Need? - Yonglong Tian; Yue Wang 041; Dilip Krishnan; Joshua B. Tenenbaum; Phillip Isola (ECCV (14), 2020)

Fantastic Generalization Measures and Where to Find Them. - Yiding Jiang; Behnam Neyshabur; Hossein Mobahi; Dilip Krishnan; Samy Bengio (ICLR, 2020)

Contrastive Representation Distillation. - Yonglong Tian; Dilip Krishnan; Phillip Isola (ICLR, 2020)

Supervised Contrastive Learning. - Prannay Khosla; Piotr Teterwak; Chen Wang 050; Aaron Sarna; Yonglong Tian; Phillip Isola; Aaron Maschinot; Ce Liu 001; Dilip Krishnan (NeurIPS, 2020)

What Makes for Good Views for Contrastive Learning? - Yonglong Tian; Chen Sun 002; Ben Poole; Dilip Krishnan; Cordelia Schmid; Phillip Isola (NeurIPS, 2020)

Understanding Invariance via Feedforward Inversion of Discriminatively Trained Classifiers. - Piotr Teterwak; Chiyuan Zhang; Dilip Krishnan; Michael C. Mozer (ICML, 2021)

Unsupervised Disentanglement without Autoencoding: Pitfalls and Future Directions. - Andrea Burns; Aaron Sarna; Dilip Krishnan; Aaron Maschinot (CoRR, 2021)

Contrastive Multiview Coding for Enzyme-Substrate Interaction Prediction. - Apurva Kalia; Dilip Krishnan; Soha Hassoun (CoRR, 2021)

Object-Aware Cropping for Self-Supervised Learning. - Shlok Mishra; Anshul Shah; Ankan Bansal; Abhyuday Jagannatha; Abhishek Sharma 001; David Jacobs 001; Dilip Krishnan (CoRR, 2021)

Pyramid Adversarial Training Improves ViT Performance. - Charles Herrmann; Kyle Sargent; Lu Jiang 004; Ramin Zabih; Huiwen Chang; Ce Liu 001; Dilip Krishnan; Deqing Sun (CVPR, 2022)

A simple, efficient and scalable contrastive masked autoencoder for learning visual representations. - Shlok Mishra; Joshua Robinson 001; Huiwen Chang; David Jacobs 001; Aaron Sarna; Aaron Maschinot; Dilip Krishnan (CoRR, 2022)

Object-aware Cropping for Self-Supervised Learning. - Shlok Kumar Mishra; Anshul Shah; Ankan Bansal; Janit Anjaria; Abhyuday N. Jagannatha; Abhishek Sharma 001; David Jacobs 001; Dilip Krishnan (Trans. Mach. Learn. Res., 2022)

MAGE: MAsked Generative Encoder to Unify Representation Learning and Image Synthesis. - Tianhong Li; Huiwen Chang; Shlok Kumar Mishra; Han Zhang 010; Dina Katabi; Dilip Krishnan (CVPR, 2023)

Muse: Text-To-Image Generation via Masked Generative Transformers. - Huiwen Chang; Han Zhang 010; Jarred Barber; Aaron Maschinot; José Lezama; Lu Jiang 004; Ming-Hsuan Yang 001; Kevin Patrick Murphy; William T. Freeman; Michael Rubinstein; Yuanzhen Li; Dilip Krishnan (ICML, 2023)

Improving CLIP Training with Language Rewrites. - Lijie Fan; Dilip Krishnan; Phillip Isola; Dina Katabi; Yonglong Tian (NeurIPS, 2023)

StyleDrop: Text-to-Image Synthesis of Any Style. - Kihyuk Sohn; Lu Jiang 004; Jarred Barber; Kimin Lee; Nataniel Ruiz; Dilip Krishnan; Huiwen Chang; Yuanzhen Li; Irfan Essa; Michael Rubinstein; Yuan Hao; Glenn Entis; et al. (NeurIPS, 2023)

StableRep: Synthetic Images from Text-to-Image Models Make Strong Visual Representation Learners. - Yonglong Tian; Lijie Fan; Phillip Isola; Huiwen Chang; Dilip Krishnan (NeurIPS, 2023)

Steerable Equivariant Representation Learning. - Sangnie Bhardwaj; Willie McClinton; Tongzhou Wang 001; Guillaume Lajoie; Chen Sun 002; Phillip Isola; Dilip Krishnan (CoRR, 2023)

StyleDrop: Text-to-Image Generation in Any Style. - Kihyuk Sohn; Nataniel Ruiz; Kimin Lee; Daniel Castro Chin; Irina Blok; Huiwen Chang; Jarred Barber; Lu Jiang 004; Glenn Entis; Yuanzhen Li; Yuan Hao; Irfan Essa; et al. (CoRR, 2023)

Substance or Style: What Does Your Image Embedding Know? - Cyrus Rashtchian; Charles Herrmann; Chun-Sung Ferng; Ayan Chakrabarti; Dilip Krishnan; Deqing Sun; Da-Cheng Juan; Andrew Tomkins (CoRR, 2023)

Improve Supervised Representation Learning with Masked Image Modeling. - Kaifeng Chen; Daniel Salz; Huiwen Chang; Kihyuk Sohn; Dilip Krishnan; Mojtaba Seyedhosseini (CoRR, 2023)

CSI: Contrastive data Stratification for Interaction prediction and its application to compound-protein interaction prediction. - Apurva Kalia; Dilip Krishnan; Soha Hassoun (Bioinform., 2023)

Scaling Laws of Synthetic Images for Model Training ... for Now. - Lijie Fan; Kaifeng Chen; Dilip Krishnan; Dina Katabi; Phillip Isola; Yonglong Tian (CVPR, 2024)

Learning Vision from Models Rivals Learning Vision from Data. - Yonglong Tian; Lijie Fan; Kaifeng Chen; Dina Katabi; Dilip Krishnan; Phillip Isola (CVPR, 2024)

Denoising Vision Transformers. - Jiawei Yang 002; Katie Z. Luo; Jiefeng Li; Congyue Deng; Leonidas J. Guibas; Dilip Krishnan; Kilian Q. Weinberger; Yonglong Tian; Yue Wang 041 (ECCV (85), 2024)

Leveraging Unpaired Data for Vision-Language Generative Models via Cycle Consistency. - Tianhong Li; Sangnie Bhardwaj; Yonglong Tian; Han Zhang 010; Jarred Barber; Dina Katabi; Guillaume Lajoie; Huiwen Chang; Dilip Krishnan (ICLR, 2024)

JESTR: Joint Embedding Space Technique for Ranking Candidate Molecules for the Annotation of Untargeted Metabolomics Data. - Apurva Kalia; Dilip Krishnan; Soha Hassoun (CoRR, 2024)